Low-frequency conductivity tensor imaging with a single current injection using DT-MREIT

Abstract

Diffusion tensor-magnetic resonance electrical impedance tomography (DT-MREIT) is an imaging modality to obtain low-frequency anisotropic conductivity distribution employing diffusion tensor imaging and MREIT techniques. DT-MREIT is based on the linear relationship between the conductivity and water self-diffusion tensors in a porous medium, like the brain white matter. Several DT-MREIT studies in the literature provide cross-sectional anisotropic conductivity images of tissue phantoms, canine brain, and the human brain. In these studies, the conductivity tensor images are reconstructed using the diffusion tensor and current density data acquired by injecting two linearly independent current patterns. In this study, a novel reconstruction algorithm is devised for DT-MREIT to reconstruct the conductivity tensor images using a single current injection. Therefore, the clinical applicability of DT-MREIT can be improved by reducing the total acquisition time, the number of current injection cables, and contact electrodes to half by decreasing the number of current injection patterns to one. The proposed method is evaluated utilizing simulated measurements and physical experiments. The results obtained show the successful reconstruction of the anisotropic conductivity distribution using the proposed single current DT-MREIT.

Stability of the isotropic conductivity reconstruction using magnetic resonance electrical impedance tomography (MREIT)

“…[46] provide the convergence theory of the single current harmonic B z algorithm in C 1 space. For one current MREIT, please also refer to [19,26] for isotropic and [29] for anisotropic conductivity reconstruction algorithms.…”

Volumetric measurements of weak current–induced magnetic fields in the human brain at high resolution

“…These modulated phase images can then be used to determine the strength and distribution of the current-induced magnetic fields and to reconstruct the underlying current flow. [5][6][7][8][9][10][11][12][13][14] Initial successful MRCDI studies in phantoms, animals, and human limbs in vivo [13][14][15][16][17][18][19][20][21][22][23][24][25][26][27][28][29][30][31] formed the basis for more recent in vivo measurements in human brain. [32][33][34][35][36] However, accurate current flow mapping in the brain remains very challenging for several reasons: First, because the measured current-induced magnetic fields are below 1-2 nT due to safety and tolerability limits of about 1-2 mA for the TES currents, 37 thermal and physiological noise as well as instrumental instabilities result in low SNR.…”

“…Initial successful MRCDI studies in phantoms, animals, and human limbs in vivo 13–31 formed the basis for more recent in vivo measurements in human brain 32–36 . However, accurate current flow mapping in the brain remains very challenging for several reasons: First, because the measured current‐induced magnetic fields are below 1–2 nT due to safety and tolerability limits of about 1–2 mA for the TES currents, 37 thermal and physiological noise as well as instrumental instabilities result in low SNR.…”

A Preliminary Study on Non-Invasive Detection of Electrical Stimulation Current Based on Magneto-Acoustic Effect

“…Based on the same principle, Zhang et al applied it to EIT and proposed MREIT [22]. MRCDI and MREIT methods improve the ill-condition to a certain extent [24], but this method has high requirements on the uniformity of magnetic field, and in the process of electrical stimulation, the spatial induction magnetic field generated by the stimulator and cable electrode will affect the detection and imaging results, and the high cost of MR equipments also limits its application. Therefore, the study of a new non-invasive detection and imaging method for the current density distribution of neural electrical stimulation is of great significance to monitor the current distribution of stimulation, solve the problem of low imaging accuracy of current stimulation, and optimize the stimulation parameters.…”